moving beyond widgets : measuring for outcomes in social services
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Moving Beyond Widgets : Measuring for Outcomes in Social Services. The AIDS Foundation of Chicago Experience David Munar and Keri Rainsberger Michael Reese Health Trust Health Care Issues Roundtable February 24, 2012. AIDS Foundation of Chicago. - PowerPoint PPT PresentationTRANSCRIPT
Moving Beyond Widgets : Measuring for Outcomes in
Social ServicesThe AIDS Foundation of Chicago Experience
David Munar and Keri RainsbergerMichael Reese Health Trust Health Care Issues
RoundtableFebruary 24, 2012
The mission of the AIDS Foundation of Chicago is to lead the
fight against HIV/AIDS and improve the lives of people affected
by the epidemic.
Founded in 1985 by community activists and physicians, the
AIDS Foundation of Chicago (AFC) is a local and national leader
in the fight against HIV/AIDS. We collaborate with community
organizations to develop and improve HIV/AIDS services; fund
and coordinate prevention, care, and advocacy projects; and
champion effective, compassionate HIV/AIDS policy.
AIDS Foundation of Chicago
ClientTrack – AFC’s Client-Level Database
Client-level information on case management and supportive services
Used by the Northeastern Illinois HIV/AIDS Case Management
Cooperative and the AIDS Foundation of Chicago housing programs
Homeless Management Information Systems (HMIS)
Client-level information on homeless persons and their service needs
Required by the US Department of Housing and Urban Development
(HUD) and implemented by local continuum
AFC participates in the City of Chicago continuum database
(ServicePoint). There are also separate HMIS implementations in most
of the suburban counties and a few of the larger suburbs
Social Service Databases
Implemented and operated by the Chicago Department of Family and Support Services (DFSS) with support from many others
All HUD-funded programs are required to participate; other homeless service providers are encouraged to participate
The City of Chicago’s federal homeless funding is tied partially to the success of HMIS
AFC participates as an Interface agency by automatically uploading data on a regular basis. AFC also logs in directly to verify data was imported correctly
City of Chicago HMIS
ClientTrack: Multiple Partners and Users
ClientTrack
26 grants
258 users
37 agencies
13 programs
ClientTrack: Capturing Service Encounter and Outcomes Data
ClientTrack
Service Plans
Services and Referrals
Medical Indicators
Assessments
Tracking Client Care11/28• Initial referral• Newly
diagnosed• Assigned to
agency same day
11/29• Call setting
initial intake
12/7• Intake• Set goals to obtain
medical care and ADAP• CM calls clinic on client’s
behalf to schedule first appointment
12/16• CM receives
medical form verifying appointment and medical information
2/2• Follow-up call
from CM• Client reports
taking HIV medications
Example
This is a real example from one of our clients flowing through care. For most of our clients this flow is more complex with multiple issues being addressed.
Tracking Care at a System Level
System level uses of data
• Understand how case management is being implemented
• Able to measure how system is comparing to standards of care
• Estimate impacts of policy or procedure changes
• Estimate eligible population for new services
• Easier and more in-depth reporting
•Health (80% of 2167 clients)•Emotional Support (56%)•Medication Adherence (53%)•Mental Health (44%)•Benefits Maintenance (42%)
Most Frequently Discussed Topics
• Improve adherence to medical appointments (25% of 986 clients)
• Improve adherence to medications (24%)• Obtain dental care (21%)• Maintain ADAP assistance (16%)• Participate in Individual Counseling (14%)
Most Frequent Goals
• Oral Health (21% of 533 clients)• Housing (15%)• Food (13%)• Medication Assistance (13%)• Eye Doctor (12%)
Most Frequent Referrals
Data from July-December 2011
Service data is entered and reported to multiple databases
Integration includes both the physical sharing of the data but also policies governing the sharing
ClientTrack as a “data warehouse”
Moving Toward Data Integration
Export From ClientTrack(Currently
Done)
Import Into ClientTrack
(Current Goal)
SAMSHA
VCM
Provide
HRSA
HMIS
Opportunities abound for additional data coordination
Shared definitions and standards important
Client confidentiality in an era of increased data sharing
AFC’s Visions for Future Development:Data coordination
Client
ClientTrack
Surveillance
Medicaid
EMR
HMIS
ADAP
Assessing for outcomes Clients assessed every 6 months Researcher analyzing questions to see what outcomes we
might be able to pull from this data
Analyzing processes Where do clients hit snags in receiving needed services Is data being entered correctly
Challenges of working with administrative data Geared to users not researchers Multiple sources of entry Retrospective In the “wild” rather than a laboratory
AFC’s Visions for Future Development:Greater data analysis capabilities
Automated chart audits Implemented first stage this round Allows review of 100% of charts virtually Will be made available to agencies to do their own
interim reviews
Quality Management Reports Medical Case Management standards established Reports for users at multiple levels (case
managers, agency supervisors, AFC program coordinators)
AFC’s Visions for Future Development:Robust quality improvement process
Quality ImprovementExampl
e
Medical Case Manager Standards Developed from best practices, consultation with key
informants Based on a one year period, most standards require two
instances within the year Case Management Face-to-Face Visits (CM V) Medical Visits (Med V) Case Management Assessments (CM AS) Care Plan Development and Update (CARE P) Care Plan Has Medical Goal (MED G) Adherence Counseling Provided (ADHER) Communication between Primary Care Provider and Case Manager
(PCP C)
Case Manager Tools : To Do List
Quality ImprovementExampl
e
Case Manager Tools : Indicators Check List
Example
Agency Indicator Review
System Indicator Review (used by agencies and AFC)
Quality ImprovementExampl
e
AFC Program Coordinator indicator review
Quality ImprovementExampl
e
The “Rich Silo” effect Non-cooperation and gamesmanship between data sources creates
detailed data that is still not shared
Quality data requires culture change Requires a whole process outlook
Balancing privacy and confidentiality with increasing capabilities Consider the need to know and usefulness before collecting data Ensuring client consents and education keep up with sharing
capacity
Standardization Data can require a significant amount of recoding to be shared
across databases Ensuring programs are being integrated in a consistent way
across providers Deduplication
Challenges and lessons learned
Over 6000 clients who shared their data with us
258 users who enter and check data The AFC Research Evaluation and Data
Services, Care, and Housing Teams
Acknowledgements